On the global and linear convergence of direct extension of ADMM for 3-block separable convex minimization models

On the global and linear convergence of direct extension of ADMM for 3-block separable convex minimization models

Abstract In this paper, we show that when the alternating direction method of multipliers (ADMM) is extended directly to the 3-block separable convex minimization problems, it is convergent if one block in the objective possesses sub-strong monotonicity which is weaker than strong convexity. In part...

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Bibliographic Details
Main Authors: Huijie Sun, Jinjiang Wang, Tingquan Deng
Format: Article
Language:English
Published: SpringerOpen 2016-09-01
Series:Journal of Inequalities and Applications
Subjects:
linear convergence rate
separable convex optimization
alternating direction method of multiplier
Karush-Kuhn-Tucher (KKT) system
strong monotonicity
Online Access:http://link.springer.com/article/10.1186/s13660-016-1173-2

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http://link.springer.com/article/10.1186/s13660-016-1173-2

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